How Murky Before a VLM Knows It Cannot See? Accuracy, Confidence and Abstention on a Physical Visibility Axis
Robustness studies of vision-language models (VLMs) grade degradation on nominal severity scales ("level 1-5") that carry no physical units, and they rarely ask whether a model's confidence follows the loss of visibility. We measure accuracy, internal (token-probability) confidence, verbalized confidence and an explicit abstain option on a visibility axis in metres: fog follows the Koschmieder model, an underwater arm scales the absorption spectrum of pure water, both are applied with a monocular metric depth map, and the visibility range V is swept over eight log-spaced levels from 250 m to 1.95 m. On 1000 COCO scenes and five small open VLMs (2-5 B parameters), accuracy on a boxed-objec...
| Authors | Mochamad Rizal Fauzan, Irgi Surya |
|---|---|
| Primary category | cs.CV |
| Published | 16 October 2026 |
| Last updated at source | 16 October 2026 |
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